{
    "cells": [
        {
            "source": [
                "a=1\n",
                "a"
            ],
            "cell_type": "code",
            "outputs": [],
            "metadata": {},
            "execution_count": null
        },
        {
            "source": [
                "pip list"
            ],
            "cell_type": "code",
            "outputs": [
                {
                    "output_type": "stream",
                    "name": "stdout",
                    "text": "Package              Version   \n-------------------- ----------\nadal                 1.2.2     \naltair               4.1.0     \nappdirs              1.4.3     \nappnope              0.1.0     \nattrs                19.3.0    \nazure-common         1.1.25    \nazure-kusto-data     0.0.44    \nazure-kusto-ingest   0.0.44    \nazure-storage-blob   2.1.0     \nazure-storage-common 2.1.0     \nazure-storage-queue  2.1.0     \nbackcall             0.1.0     \nbeakerx              1.4.1     \nblack                19.10b0   \nbleach               3.1.4     \nbqplot               0.12.6    \nbranca               0.3.1     \ncertifi              2020.4.5.1\ncffi                 1.14.0    \nchardet              3.0.4     \nclick                7.1.2     \ncryptography         2.9.2     \ncycler               0.10.0    \ndebugpy              1.0.0b7   \ndecorator            4.4.2     \ndefusedxml           0.6.0     \nentrypoints          0.3       \nidna                 2.9       \nipydatawidgets       4.0.1     \nipykernel            5.2.1     \nipyleaflet           0.12.4    \nipython              7.13.0    \nipython-genutils     0.2.0     \nipyvolume            0.5.2     \nipywebrtc            0.5.0     \nipywidgets           7.5.1     \nisodate              0.6.0     \njedi                 0.17.0    \nJinja2               2.11.2    \njson5                0.9.5     \njsonschema           3.2.0     \njupyter-client       6.1.3     \njupyter-core         4.6.3     \njupyterlab           2.1.3     \njupyterlab-server    1.1.5     \nK3D                  2.7.4     \nkiwisolver           1.2.0     \nMarkupSafe           1.1.1     \nmatplotlib           3.2.1     \nmistune              0.8.4     \nmsrest               0.6.13    \nmsrestazure          0.6.3     \nnbconvert            5.6.1     \nnbformat             5.0.5     \nnglview              2.7.5     \nnotebook             6.0.3     \nnumpy                1.18.2    \noauthlib             3.1.0     \npandas               1.0.3     \npandocfilters        1.4.2     \nparso                0.7.0     \npathspec             0.8.0     \npexpect              4.8.0     \npickleshare          0.7.5     \nPillow               7.1.1     \npip                  19.2.3    \nprometheus-client    0.7.1     \nprompt-toolkit       3.0.5     \nptyprocess           0.6.0     \npy4j                 0.10.9    \npycparser            2.20      \nPygments             2.6.1     \nPyJWT                1.7.1     \npyparsing            2.4.7     \npyrsistent           0.16.0    \npython-dateutil      2.8.1     \npythreejs            2.2.0     \npytz                 2019.3    \npyzmq                19.0.0    \nqgrid                1.1.1     \nregex                2020.4.4  \nrequests             2.23.0    \nrequests-oauthlib    1.3.0     \nSend2Trash           1.5.0     \nsetuptools           41.2.0    \nsix                  1.14.0    \nterminado            0.8.3     \ntestpath             0.4.4     \ntoml                 0.10.0    \ntoolz                0.10.0    \ntornado              6.0.4     \ntraitlets            4.3.3     \ntraittypes           0.2.1     \ntyped-ast            1.4.1     \nurllib3              1.25.9    \nvega-datasets        0.8.0     \nwcwidth              0.1.9     \nwebencodings         0.5.1     \nwidgetsnbextension   3.5.1     \nxarray               0.15.1    \nNote: you may need to restart the kernel to use updated packages.\n"
                }
            ],
            "metadata": {
                "tags": ["WOW"]
            },
            "execution_count": 3
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "# HELLO WORLD"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 1,
            "metadata": {},
            "outputs": [
                {
                    "output_type": "error",
                    "ename": "SyntaxError",
                    "evalue": "invalid syntax (<ipython-input-1-8b7c24be1ec9>, line 1)",
                    "traceback": [
                        "\u001b[0;36m  File \u001b[0;32m\"<ipython-input-1-8b7c24be1ec9>\"\u001b[0;36m, line \u001b[0;32m1\u001b[0m\n\u001b[0;31m    with Error\u001b[0m\n\u001b[0m              ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n"
                    ]
                }
            ],
            "source": [
                "with Error"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 6,
            "metadata": {},
            "outputs": [
                {
                    "output_type": "display_data",
                    "data": {
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\n"
                    },
                    "metadata": {
                        "needs_background": "light"
                    }
                }
            ],
            "source": [
                "import matplotlib\n",
                "import matplotlib.pyplot as plt\n",
                "import numpy as np\n",
                "\n",
                "t = np.arange(0.0, 2.0, 0.01)\n",
                "s = 1 + np.sin(2 * np.pi  * t)\n",
                "\n",
                "fig, ax = plt.subplots()\n",
                "ax.plot(t, s)\n",
                "\n",
                "ax.set(xlabel='time (s)', ylabel='voltage (mV)',\n",
                "    title='About as simple as it gets, folks')\n",
                "\n",
                "ax.grid()\n",
                "\n",
                "fig.savefig('test.png')\n",
                "\n",
                "plt.show()"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [],
            "source": []
        }
    ],
    "metadata": {
        "language_info": {
            "name": "python",
            "codemirror_mode": {
                "name": "ipython",
                "version": 3
            }
        },
        "orig_nbformat": 2,
        "file_extension": ".py",
        "mimetype": "text/x-python",
        "name": "python",
        "npconvert_exporter": "python",
        "pygments_lexer": "ipython3",
        "version": 3,
        "kernelspec": {
            "name": "python_defaultSpec_1591908362720",
            "display_name": "Python 3.8.2 64-bit ('venvForWidgets': venv)"
        }
    },
    "nbformat": 4,
    "nbformat_minor": 2
}
